{"product_id":"9783319120805","title":"Springer Theses","description":"\u003ch1\u003eSpringer Theses\u003c\/h1\u003e \u003ch2\u003eNasrollahi, Nasrin\u003c\/h2\u003e \u003cp\u003e\u003c\/p\u003e\u003cp\u003eThis thesis transforms satellite precipitation estimation through the integration of a multi-sensor, multi-channel approach to current precipitation estimation algorithms, and provides more accurate readings of precipitation data from space.\u003c\/p\u003e\u003cp\u003eUsing satellite data to estimate precipitation from space overcomes the limitation of ground-based observations in terms of availability over remote areas and oceans as well as spatial coverage. However, the accuracy of satellite-based estimates still need to be improved.\u003c\/p\u003e\u003cp\u003eThe approach introduced in this thesis takes advantage of the recent NASA satellites in observing clouds and precipitation. In addition, machine-learning techniques are also employed to make the best use of remotely-sensed \"big data.\" The results provide a significant improvement in detecting non-precipitating areas and reducing false identification of precipitation.\u003c\/p\u003e \u003ch3\u003eDetails\u003c\/h3\u003e \u003cp\u003ePublished by: Springer\u003c\/p\u003e \u003cp\u003ePublication Date: 2014-11-27\u003c\/p\u003e \u003cp\u003eFormat: Hardcover\u003c\/p\u003e \u003cp\u003eISBN-13: 9783319120805\u003c\/p\u003e \u003cp\u003eDOI: 10.1007\/978-3-319-12081-2\u003c\/p\u003e \u003cp\u003eDimensions: 235cm x155cm\u003c\/p\u003e \u003cp\u003ePages: 68\u003c\/p\u003e ","brand":"Springer International Publishing","offers":[{"title":"Default Title","offer_id":47393641758860,"sku":"9783319120805","price":98.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9783319120805.jpg?v=1775768636","url":"https:\/\/lateknightbooks.com\/products\/9783319120805","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}